This invention relates generally to portfolio management systems, the primary markets discussed in detail herein are the publicly-traded stock markets. However, the invention can be used to trade on other public markets (e.g., FOREX, commodities, options, etc.). Therefore, for the examples and discussion will use the U.S. publicly-traded stock market.
For many years, there have been two different schools of thought regarding stock market trading. The prevailing school preaches a detailed analysis of a company's financial reports and activities to determine an actual value of the shares of stock or Individually Traded Units (ITU) of the company. If the current market price of the company's total outstanding ITU's is lower than the computed actual value, then the ITU price will probably increase. If the current market price is higher, then the ITU price will probably decrease. This predictive technique is flawed in that the current market price is affected by many other factors such as supply and demand, world events, expected earnings vs. actual earnings, etc. The general worth of a broker that uses this school of thought is determined by his intuitive abilities to take all of these factors into account to attain more accurate predictions than his or her competition.
The second, and for many years the less prevalent school of thought preaches an analysis technique known as technical trading. Generally, technical traders perform very little analysis of the company's financial reports and activities. They watch the current market price with a given frequency in order to determine pricing trends. If the price of an ITU (correcting for minor fluctuations) has been increasing for a long time period in the past and into the present, then it will probably continue to increase for at least a short time period in the future. Conversely, a past long-term trend of decreasing prices tend to forecast a continuation of falling prices. For many years prior to the computer information age, technical traders would graph the stock prices for a given company over time. Most frequently, they would use the daily closing market price to plot discreet points on a graph. They would then plot trend lines in an effort to predict the future price of an ITU. FIG. 1 shows an upward price trend, while FIG. 2 shows a downward price trend. Note the use of the trend line to compensate for daily fluctuations. Technical traders would use these trend lines to predict the future price. Trend lines were used as a method of linearly “smoothing” the graph (i.e., disregarding pricing fluctuation over a long time period). Often the price graph would show familiar patterns. One such pattern is the “head and shoulders” illustrated in FIG. 3. Here, a series of upward and downward trends merge into a general upward trend to form a “head” and two “shoulders,” and a downward trend develops from the second “shoulder.” Typically, such a pattern results in a long-term downward trend during the time period following the formation of the second “shoulder.” There is no logical reason for this to occur. However, past experience with this type of pattern provides a strong prediction for future pricing of the ITU. An entire repertoire of pricing patterns exist for the technical trader to use in order to predict future pricing.
For many years prior to the application of computers to technical trading, traders needed to be satisfied with ITU pricing sample points taken only from closing market prices. However, computer technology presented technical traders with the opportunity to sample pricing points much more frequently. Today, sampling intervals of minutes or seconds are used. The availability of the larger number of data samples permitted technical traders to develop sophisticated computer software to more accurately predict pricing trends. Based upon these trends, short-term recommendations could be made by technical trading brokers to customers to buy, sell, or hold a given stock.
Upon review of the existing state of the art as represented by issued patents and published applications it should be noted that computerized systems implementing investment strategies that analyze each separate stock within a portfolio to determine if the present trading price should be used to either buy, hold, or sell additional shares of that stock have been the subject of several earlier patent documents.
Of particular interest is the patent application publication US 2005/0154658 to Bove et al., which describes a system for automatic investment planning using a computerized scheme that automates investment planning for a client. In the scheme, data regarding the client's desired asset allocation, current asset portfolio and preferred domain (e.g., stocks, bonds, etc.) are input into a computer for processing. The data are used to automatically generate financial transaction recommendations for modifying the client's current asset portfolio to reach as close as possible, the desired asset allocation and the preferred domain. The generated recommendations include specific recommendations for selling amounts of selected current assets and specific recommendations for buying amounts of one or more investment funds. The recommendations are displayed on a summary report for review by the client or the client's financial manager, or the recommendations are electronically communicated to a trade execution computer which automatically performs the necessary transactions to execute the buy/sell recommendations. The recommendations are selected in a manner which minimizes the tax impacts and transaction costs of potential sell transactions.
Furthermore, the U.S. Pat. No. 6,484,152, issued to Robinson, shows a method of automatically selecting a securities portfolio from a plurality of securities, selecting investment characteristics and investment limits considered important for investment objectives. The method establishes a safety level for the portfolio constructing a matrix having entries corresponding to: (a) the selected characteristics and limits; and, (b) the candidate securities; thereby establishing an objective function corresponding to the constructed matrix and then determining the securities portfolio based on the matrix and the objective function. The investment characteristics may include dividends, rate of growth of earnings, financial strength, safety, predictability of earnings, and performance rankings provided by an advisory service. The safety level may be provided by determining a number of different stocks to be included in the specific portfolio. The selected investments may be determined by limitations imposed on the amount of investment in each candidate security. At least one selected investment limit may relate to a standardized commercial rating or a measure of financial strength.
In addition, the patent application publication US 2005/0234809, issued to Criner, describes a method that, given a price-time trajectory, seeks the policies that optimize portfolio performance over that trajectory. The method is based on the result of a program of research that succeeded in portfolio optimization. A controlled theoretic approach included: 1) developing a measure of profitability of the trading portfolio; 2) computationally modeling the trading process operating on the price-time histories; 3) calculating estimates of the price-time histories using functions with well-known mathematical characteristics; 4) calculating, using the calculated estimates, derived functions of the price-time histories about which control variables are known and about which there is prior knowledge; and 5) simulating, using the derived functions, the trading policies and seeking the values of the control variables that maximize the portfolio's trading performance over the life of the trades.
The above-listed references were selected to illustrate patent documents in the field of formula investment strategies that analyze each separate stock within a portfolio to determine if the present trading price should be used to determine whether to: buy, hold, or sell additional shares.